Fraud Patterns Analyst
Stripe · US-Remote
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Job description
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world's largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
About the team
The Risk Operations team is looking for an experienced fraud analyst to join an industry-leading global fraud operations team. This position is responsible for writing and maintaining fraud rulesets to prevent transaction fraud, conducting data analysis to identify and mitigate fraud attacks, while minimizing impact to users, and working collaboratively with fraud, operations, and product stakeholders to proactively implement fraud strategies and controls. They should have a deep understanding of fraud patterns and typologies, advanced SQL proficiency, strong analytical abilities, and experience writing and managing fraud rulesets.
What you'll do
Did you know that only around 4% of the world's GDP comes from internet commerce? At Stripe, we believe that this represents a future with almost limitless potential for innovation, creativity, and global prosperity. While the promise of a global online economy is palpable, it doesn't come without significant risk. Each day, bad actors disrupt the trust and safety of the internet and increase the barrier of entry for online businesses. Before we can fully realize the potential of a global internet economy, we must first address the burgeoning problem of fraud.
We are looking for someone passionate about fighting fraud, identifying new trends and typologies, conducting complex data analysis, and working collaboratively with peers and partners in the fraud space. This position works closely with cross-functional stakeholders across product, engineering, data science, and operations to identify and mitigate risk from complex, distributed transaction fraud attacks.
The right candidate for this role will have a minimum of five years' experience conducting advanced data analysis
Responsibilities
Did you know that only around 4% of the world's GDP comes from internet commerce? At Stripe, we believe that this represents a future with almost limitless potential for innovation, creativity, and global prosperity. While the promise of a global online economy is palpable, it doesn't come without significant risk. Each day, bad actors disrupt the trust and safety of the internet and increase the barrier of entry for online businesses. Before we can fully realize the potential of a global internet economy, we must first address the burgeoning problem of fraud.
We are looking for someone passionate about fighting fraud, identifying new trends and typologies, conducting complex data analysis, and working collaboratively with peers and partners in the fraud space. This position works closely with cross-functional stakeholders across product, engineering, data science, and operations to identify and mitigate risk from complex, distributed transaction fraud attacks.
The right candidate for this role will have a minimum of five years' experience conducting advanced data analysis using SQL, preferably within the fraud space across e-commerce, payments, or cryptocurrency. Candidates should have experience writing, maintaining, and analyzing complex fraud rulesets and demonstrated success minimizing fraud losses along with impacts to users. Candidates should also have experience working closely with product teams to implement risk controls and demonstrate a deep understanding of fraud typologies, controls, and ability to mitigate fraud risk.
• Build and maintain fraud rulesets to prevent transaction-level fraud losses, including ongoing monitoring and measurements of precision and recall
• Conduct advanced data analysis of structured and unstructured data sets to proactively identify emerging fraud attacks impacting Stripe and its users
• Collaborate closely with product, risk, and operations teams to proactively identify and mitigate fraud exposure
• Investigate, conduct root cause analysis, and deploy remediations to prevent future complex and distributed fraud attacks
• Investigate and take action against anomalous clusters of transactions based on account activity, processing volume, or other risk indicators while minimizing negative impacts to Stripe users
• Respond to incidents involving complex fraud schemes to quickly mitigate exposure to Stripe, its users, and financial partners
• Utilize analytics to identify and implement initiatives to automate manual processes and workload across the organization
• Create visualizations, dashboards, and queries to drive visibility and oversight into impact, performance, loss risks, and user experience
• Utilize Stripe tools and systems to enable systematic actioning of fraudulent merchants, maintaining an extremely high level of accuracy to prevent negative user experience
Requirements
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
• A minimum of five years of experience conducting advanced data analysis and managing transaction fraud rulesets
• Advanced-level proficiency in SQL
• Experience working closely with modeling, data science, and intelligence stakeholders to implement automatic and scaled controls and processes
• Experience creating data visualizations and dashboards and presenting findings to technical and non-technical audiences, including senior leadership
• The ability to drive execution on projects working in a heavily cross-functional environment
• Creativity, a team-focused mentality, and effective problem-solving skills
• The ability and desire to question the status quo
• The ability to approach challenges from a user perspective while being pragmatic and solutions-oriented
• Fraud experience in payments, e-commerce, fintechs, or cryptocurrency mitigating digital and card-not-present fraud
• Proficiency in Splunk, Python, Tableau, or other data visualization tools
• Undergraduate or advanced degree in analytics, data science, or statistics